'Dirty data will cost businesses money and time over the next two years with more than 25 per cent of all critical information used by Fortune 1000 companies having flaws', according to analyst Gartner.

'Flawed data includes information that is inaccurate, incomplete or duplicated, creating significant and unnecessary costs for companies, it said. If the quality of customer data is poor, this can lead to higher customer turnover, missed sales opportunities and excessive expenses from customer contact processes such as mailouts.'

'Business areas such as budgeting, manufacturing and distribution can also be severely affected by dirty data.'

As can be seen by Gartner's analysis, the impact of poor data is more than just a 'wastage' issue.

Yet direct marketers are still seduced by low CPM rates, even if it means sourcing intrinsically less well profiled data, less regularly updated with embedded higher rates of churn.

Whilst good quality data can be 100% more expensive than generic and poorly maintained sources, the overall cost this represents of a campaign is modest, and the impact on medium term ROI is rather more significant.

When it comes to enhancing an in-house database, why wouldn't a savvy marketer best the very best available to increase accuracy, segmentability and targeting relevancy to their customer data?

One wouldn't wear dirty laundry to work after all? Why then would you pay for it?